Question 2 (11 marks) The most common theory explaining global warming relates an increase in atmospheric levels of carbon dioxide (CO2), a greenhouse gas, to increases in temperature. Data about two variables were collected: the mean annual CO2 concentration in the atmosphere, measured in parts per million (ppm), and the mean annual air temperature across the globe, measured in degrees Celsius. A regression predicting temperature from CO2 concentration using the above data produced the following output table. Both coefficients were found to be statistically significant. Dependent variable is: Temperature R-squared = 64.1% Variable Intercept CO2 Coefficient 15.21 0.020 a) What percentage of variability in the temperature does this model explain? (2 marks) b) Give the regression equation. Name variables clearly. (2 marks) c) What is the meaning of the slope in this equation? (2 marks) d) If CO2 levels reach 410 ppm, what mean temperature would the regression model predict? (2 marks) e) How would you check whether a regression model is appropriate for this analysis? (3 marks)